Predicting the immunological nonresponse to antiretroviral therapy in people living with HIV: a machine learning-based multicenter large-scale study

Predicting the immunological nonresponse to antiretroviral therapy in people living with HIV: a machine learning-based multicenter large-scale study

BackgroundAlthough highly active antiretroviral therapy (HAART) has greatly enhanced the prognosis for people living with HIV (PLWH), some individuals fail to achieve adequate immune reconstitution, known as immunological nonresponse (INR), which is linked to poor prognosis and higher mortality. How...

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Bibliographic Details
Main Authors: Suling Chen, Lixia Zhang, Jingchun Mao, Zhe Qian, Yuanhui Jiang, Xinrui Gao, Mingzhu Tao, Guangyu Liang, Jie Peng, Shaohang Cai
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-03-01
Series:Frontiers in Cellular and Infection Microbiology
Subjects:
HIV/AIDS
CD4+ T cell counts
highly active antiretroviral therapy
immune reconstitution
immunological nonresponse
Online Access:https://www.frontiersin.org/articles/10.3389/fcimb.2025.1466655/full
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https://www.frontiersin.org/articles/10.3389/fcimb.2025.1466655/full

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